403 results about "Heat transfer model" patented technology

The invention provides a power plant heat tracing system intelligent optimization method based on environment temperature fluctuation, and relates to the technical field of temperature control of a power plant heat tracing system, and the method comprises the following steps: S1, data collection and preprocessing: deploying a sensor array, collecting an operation data signal # imgabs0 # of a power plant heat tracing pipeline, carrying out the preprocessing of the operation data signal # imgabs1 #, and storing the preprocessed operation data signal # imgabs0 #; outputting a standardized feature vector; s2, model establishment and parameter optimization: constructing a physical-data dual-drive heat transfer model, and inputting standardized feature vector optimization initial parameters; compared with the prior art, the method has the following beneficial effects: firstly, control parameters can be automatically adjusted according to factors such as thermal load change, external environment temperature fluctuation and equipment aging; and secondly, the temperature trend in the future short time can be predicted by constructing a heat transfer dynamic model, the control strategy is adjusted in advance, the temperature is prevented from being out of control, heat dissipation can be increased in advance or heat source input can be adjusted in advance, and safe and efficient operation of the system is effectively guaranteed.

The invention relates to the technical field of industrial control, and discloses a dry-wet combined cooling tower operation state prediction and diagnosis system comprising a load prediction module used for obtaining production plan data and environment information, constructing a basic heat load prediction model, and outputting a total prediction heat load; the thermal modeling module is used for establishing a heat transfer model and an energy consumption model, the heat transfer model outputs cooling amounts in different operation modes, and the energy consumption model outputs total predicted power; the dry-wet decision module is used for constructing a multi-objective optimization function and solving the multi-objective optimization function to obtain a dry-wet switching strategy; and the control execution module is used for executing the dry-wet switching strategy. According to the method, the basic thermal load prediction model is established, so that the prediction precision of the thermal load is improved, and differentiated cooling strategies are provided for different production stages; on the basis of real-time load requirements and environmental conditions, a dry mode or a wet mode is intelligently selected for operation, and a multi-objective optimization function is constructed, so that the balance between cooling requirement meeting and system energy consumption minimization is realized.

The invention relates to a multi-cell control method for hydrogen production alkaline electrolytic cells based on nonlinear model predictive control, which belongs to the technical field of hydrogen production and comprises the following steps of: performing data acquisition on key positions of a hydrogen production alkaline electrolytic cell system in real time; based on the dynamically determined priority of each electrolytic cell, dynamic load distribution of each electrolytic cell is carried out, and a multi-dimensional cooperative regulation strategy is implemented to obtain a hydrogen yield target value of each electrolytic cell; constructing a nonlinear model comprising an electrolytic reaction model, a heat transfer model and an inter-tank coupling model, and performing parameter identification and verification; and designing a nonlinear model predictive control algorithm, performing discretization processing on the nonlinear model, introducing Kalman filtering to process the uncertainty of the model, taking a corresponding hydrogen yield target value reached by each electrolytic cell on the premise of meeting the constraint as a final control target, constructing an optimized target function, and performing solving to obtain an optimal control scheme. Compared with the prior art, the control precision and the system stability can be effectively improved.

The invention belongs to the technical field of fine chemical reaction safety testing and automatic chemistry, and particularly discloses a nonlinear model predictive temperature control method of a semiconductor temperature control type synthesis reactor. The method comprises the following steps: constructing a dynamic heat transfer model of the system based on the semiconductor temperature control type synthesis reactor; designing a nonlinear model prediction controller according to the heat transfer model of the synthesis reactor; constructing a multi-constraint objective function for nonlinear predictive control according to the characteristics of the controlled object; and solving an optimal control sequence for the nonlinear model prediction controller by adopting a projection gradient method. Compared with a traditional PID temperature control algorithm, the temperature of the reactor can be accurately predicted and controlled through the designed nonlinear model prediction temperature control algorithm, it is ensured that the chemical reaction is conducted at the optimal temperature, and the robustness and adaptability of a control system are improved.

The invention discloses an adaptive gradient enhanced Kriging agent modeling method suitable for spacecraft heat transfer model correction, and relates to the field of spacecraft heat transfer model correction. The method specifically comprises the following steps: S1, carrying out theoretical derivation construction on a related core function in a self-adaptive gradient enhancement modeling process of a gradient weighted Gaussian process prediction function and a target sample self-adaptive learning function Kriging; and S2, establishing a novel adaptive gradient enhanced Kriging proxy model of the spacecraft heat transfer model through a numerical method based on a proxy model related core function constructed by theoretical derivation in the step S1. The operation complexity that an adjoint function and a Taylor equation need to be solved in traditional gradient enhancement agent modeling is avoided, the gradient enhancement method is embedded into the iteration process of adaptive learning, and efficiency and accuracy are improved.

The invention provides a lithium ion battery core temperature prediction method based on a finite element model, and the method comprises the following steps: 1, designing an electrochemical test experiment, and constructing a one-dimensional electrochemical model containing a lithium ion battery electrochemical heat production mechanism; 2, designing a lithium ion battery temperature test experiment, obtaining electrochemical parameters, heat transfer characteristic parameters, internal thermophysical parameters and environmental parameters of the battery under different working conditions, and obtaining a temperature change curve of the center position and the surface of the battery; and step 3, based on the heat balance equation, establishing a three-dimensional heat transfer model having the same geometric characteristics as the battery used in the experiment. According to the experimental result in the step 2, the three-dimensional heat transfer model is subjected to non-uniform region division, each region corresponds to one one-dimensional electrochemical model, and the heat production rate per unit volume is calculated by the one-dimensional electrochemical model in the step 1; introducing the heat production rate of each area into a three-dimensional heat transfer model to calculate the temperature distribution of the battery, and designing an experiment to correct a one-dimensional electrochemical model; 4, modifying the operation conditions and heat dissipation conditions of the battery, and calculating and analyzing the temperature difference delta T between the center position and the surface position of the battery under different operation conditions and heat dissipation conditions by using the three-dimensional heat transfer model in the step 3; and 5, measuring the surface temperature of the battery, and calculating the temperature of the center of the battery according to the working condition of the battery in the step 4 and the delta T corresponding to the environment temperature, thereby realizing monitoring of the temperature of the center position of the battery. According to the method, a high-precision algorithm model is constructed and verified by utilizing data accumulated in an earlier-stage experiment, the central point temperature which is difficult to directly measure in the battery is predicted only through real-time and easily-acquired battery surface temperature information, operation condition parameters and heat dissipation conditions, key thermal state information is provided for a battery management system, and the battery management efficiency is improved. The method is used for real-time safety monitoring and thermal management optimization.

The invention discloses a lithium battery thermal parameter online monitoring method and equipment. According to the method, a one-dimensional heat transfer model of the battery is established, and a finite element model is solved by inversion of battery surface temperature change actually measured in operation, so that combined monitoring of the heat conductivity coefficient, the convective heat transfer coefficient, the average temperature and the heat production power P of the lithium battery is realized. Meanwhile, only the temperature sensor needs to be arranged on the surface of the battery, the battery does not need to be disassembled or an internal sensor does not need to be implanted, the battery integrity is kept, and the method is suitable for battery full-life-cycle monitoring. According to the method, the key thermal parameters of the lithium battery can be identified online in a non-intrusive, low-cost and high-reliability manner, support is provided for thermal management, health assessment and thermal safety early warning of the battery, and the method is suitable for various battery configurations and thermal management systems.

The invention discloses a rock-soil temperature field rapid solving method suitable for a ground source heat pump system, and the method comprises the steps: firstly building a three-dimensional unsteady-state heat transfer model in consideration of a buried pipe coaxial structure, a porous arrangement form and the characteristics of a multilayer heterogeneous soil body in the ground source heat pump system; then simulating a thermal response process by using the model, constructing a multi-domain coupled thermal conduction augmentation matrix, performing POD on the matrix, extracting a dominant mode function of a temperature field, and constructing a low-dimensional POD-based mode space; and finally, constructing a POD-Galerkin low-order model, simulating a buried pipe group soil temperature field, performing inversion of a heat source function, and outputting stratum thermophysical parameters. According to the method, the calculation efficiency and the simulation precision of the porous coupling and long-period unsteady state heat transfer process are remarkably improved, the problem that traditional finite element and finite difference methods are high in time consumption in porous strong coupling modeling is solved, and rapid prediction of the soil temperature and robust recognition of the heat source function under a complex stratum and a heat exchange structure can be achieved.

The invention belongs to the technical field of ocean engineering and water electrolysis hydrogen production. In order to solve the problems that a traditional water cooling system is large in size and low in heat dissipation efficiency, a multi-scale thermal sensing network is deployed to collect data; establishing a multi-phase-change cross-scale heat transfer model; constructing a two-stage gradient composite cooling module; constructing and optimizing a cooling decision algorithm; designing a cooperative control loop; deep reinforcement learning control is implemented; creating a functional surface; and constructing a dynamic optimization system. The characteristics of part of the steps are limited, efficient heat management can be achieved, and stable operation of the floating type offshore hydrogen production platform cooling system is guaranteed.

The invention relates to the technical field of infrared thermal imaging, in particular to a human body analysis method and system based on an infrared thermal image. The method comprises the following steps: acquiring an infrared thermal image sequence of a limb to be detected in a thermal relaxation process; segmenting the image sequence, constructing a topological center line of an effective contour, and defining a heat flow reference direction based on the geometric width change of a cross section along the center line; a temperature gradient vector field is calculated, and an area with the gradient direction and the heat flow reference direction in reverse distribution and containing a closed isotherm is screened out to serve as a thermal topology abnormal area; establishing a biological heat transfer model taking the surface temperature as a boundary condition, performing inverse solution on the thermal topology abnormal region, and performing inverse calculation on a heat source parameter corresponding to the subcutaneous depth; and when the heat source parameter exceeds a threshold value, generating a damage early warning. According to the method, by quantifying metabolic heat abnormality caused by inflammation in tissues, accurate positioning and quantitative evaluation of deep injury of limbs are realized, and the accuracy of human injury detection is remarkably improved.

The invention provides a high-strength aluminum alloy selective laser melting forming thermal stress prediction method based on deep learning. The method comprises the steps of 1, finite element model establishment and simulation, wherein a heat transfer model and a thermal coupling model are established; an SLM process is used as a simulation object, a Gaussian model is adopted to define a laser heat source, and thermal stress distribution under different process parameters and different sample sizes is simulated; wherein the process parameters comprise laser power, scanning speed and hatch spacing; step 2, data processing and deep learning model training; comprising the steps of data preprocessing, neural network model architecture determination, adversarial network part generation and model configuration and training. 3, evaluating and optimizing the model; and 4, thermal stress prediction and process optimization. By learning a complex mode in finite element simulation data through a deep learning model, efficient and accurate thermal stress prediction is achieved, and the problems that traditional finite element analysis is complex in calculation and large in resource consumption are solved.

The invention discloses a heat exchange station circulating pump characteristic adaptive optimization control method and system, and relates to the technical field of circulating pump control, and the method comprises the steps: building a building terminal heat transfer model and a building energy balance model based on the temperature distribution of the surface of a radiator, and then building a building load prediction model; performing numerical modeling on the performance curve of the heat exchange station circulating pump, and establishing a circulating pump performance model; based on a depth deterministic strategy gradient algorithm, establishing a neural network control model for self-adaptive control of the circulating pump of the heat exchange station; establishing a state, an action and a reward function of an agent of the neural network control model; and training the neural network control model to obtain a trained control model, and performing real-time control on the heat exchange station circulating pump based on the trained control model. The technical problems that a traditional control method of the circulating pump is low in operation efficiency and serious in energy waste are solved.

The invention discloses an energy shaft heat exchange efficiency optimization method based on stratum thermophysical property intelligent analysis, and the method comprises the steps: constructing a structured thermophysical property parameter database through integrating laboratory testing, on-site exploration and literature data, and covering key parameters such as a heat conductivity coefficient, specific heat capacity, a thermal diffusion coefficient and the like; a heat transfer model is verified and expanded by combining a reduced scale physical experiment and multi-parameter coupling numerical simulation; machine learning algorithms such as a random forest and a neural network are utilized to establish a nonlinear prediction model of the thermophysical parameters and the heat exchange efficiency of the energy shaft, the contribution degree of the parameters is quantified, and an adaptability threshold value is defined. Through similarity matching of drilling exploration data and a database, the optimal stratum depth is recommended, and finally a cloud intelligent platform is integrated, so that real-time data updating, online calculation and construction suggestions are realized. According to the method, the precision of stratum suitability evaluation in energy shaft ground source heat pump system development is remarkably improved, and the geothermal energy development efficiency is remarkably improved.

The present application relates to the field of fiber-reinforced resin matrix composite molding, and in particular to a thermal compensation design and implementation method for the near-net-shape molding of a thermoset composite component and based on a temperature field and a cure degree field. The method comprises: establishing a minimum symmetric unit model on the basis of the size of a component, the size of a mold, and an ambient temperature; establishing a cure kinetics model and a heat transfer model; incorporating a molding temperature profile into a subprogram; on the basis of an obtained temperature field and an obtained cure degree field, performing simulated thermal compensation on regions where the temperature is lower than a molding temperature and the temperature difference from the molding temperature is greater than or equal to 5% of the molding temperature, until the difference between the temperature of each region and the current molding temperature is lower than 5% of the molding temperature; then, performing stimulated thermal compensation on regions where the cure degree is less than or equal to 0.9; and assembling a thermal compensation apparatus on the basis of a thermal compensation design scheme, performing experimental validation, and when the difference between an actually measured temperature value and a simulated value is less than 5% and the cure degree exceeds 0.9, obtaining a thermal compensation scheme and a thermal compensation method. The blindness of traditional molding that relies on experience is reduced.

The invention relates to the technical field of power system demand side management and optimization operation, and discloses an electric heating load master-slave game collaborative optimization method based on AP clustering and adjustable potential modeling, which comprises the following steps: establishing a directly-heated electric heating indoor heat transfer model to analyze a single user to obtain load characteristics of heating users; a decentralized electric heating load refined aggregation model is constructed, and decentralized heating users are divided into different clusters; an adjustable potential quantification model is constructed, and the adjustable electric quantity and the adjustable potential of each cluster are obtained; and a heating load group optimization operation model based on the master-slave game is constructed, power grid purchase and sale electricity price information, distributed power supply cost information, adjustable electric quantity and adjustable potential are input, and a power utilization behavior adjustment strategy is obtained. According to the method, through refined house type clustering, master-slave game framework design and an improved solution algorithm, precise mining and optimized operation of the heating load group regulation potential are realized, the peak regulation pressure of a power grid is effectively reduced, and the comfort of a user is considered.

The invention relates to the technical field of intelligent construction of road engineering, and discloses an expressway asphalt pavement construction data analysis and processing system, the system performs digital modeling on an asphalt mixture and anchors the asphalt mixture to a pavement three-dimensional coordinate by creating a material state vector including a static attribute, a dynamic state and a process resume, and the system adopts a heat transfer model to construct an asphalt pavement construction data analysis and processing system. And the predicted temperature of the target vector at the future interception moment of the road roller is updated in real time and forwards simulated. Meanwhile, the system calculates a dynamic compactability window according to the compaction history and the material type, compares the predicted temperature with the window, generates a feedforward control instruction of a standard, priority or waiting operation, converts the feedforward control instruction into visual guidance, and issues the visual guidance to the vehicle-mounted terminal, so that prospective control is realized. According to the invention, the conversion of construction control from passive lag to active feedforward is realized, the fineness of the compaction process is improved, and a reliable digital quality tracing mechanism is established.

A thermal compensation design and implementation method for near-net-shape molding of a thermoset composite part based on temperature and curing degree fields is provided. A minimum symmetric unit model is established based on sizes of the part and a mold and ambient temperature. A curing kinetic model and a heat transfer model are established. A molding temperature curve is written into a subprogram. A simulated thermal compensation is performed on a region whose temperature is lower than a molding temperature with a difference of greater than or equal to 5% of the molding temperature until the temperature difference of individual regions is less than 5% of the molding temperature. The simulated thermal compensation is then performed on those regions with a curing degree less than or equal to 0.9. A thermal compensation device is assembled according to the thermal compensation scheme for experimental verification.

The invention belongs to the technical field of computer aided design, and provides a C / C composite material thermochemical response and pore scale structure evolution prediction method, which comprises the following steps: constructing a geometric model of the pore scale of a rocket engine jet pipe; establishing a fluid flow model in a D2Q9 form; establishing a multi-component mass transport model in a D2Q5 form; establishing a heat transfer model in a D2Q5 form; establishing a heterogeneous chemical reaction model of the fluid-solid boundary; establishing an updating model of the composite material based on a volume pixel method; and based on a geometric model, a fluid flow model, a multi-component mass transport model, a heat transfer model, a heterogeneous chemical reaction model and an update model, predicting the thermochemical response and pore scale structure evolution of the C / C composite material in the rocket engine nozzle. The method is provided for studying the ablation process of the C / C composite material, and theoretical basis and guidance direction are provided for thermal performance study and fine design of the spray pipe.

The invention discloses a flexible sunlight greenhouse temperature control method, system and device and a storage medium, and relates to the technical field of greenhouse environment, the method comprises the following steps: calling a heat transfer model to carry out temperature field simulation calculation according to greenhouse internal thermal field distribution data to obtain a first predicted temperature value; calling a greenhouse temperature prediction model to perform time sequence analysis on the external environment temperature historical time sequence data to obtain a second predicted temperature value; performing data fusion according to the first predicted temperature value and the second predicted temperature value to obtain a comprehensive predicted temperature value; and according to a deviation value between the comprehensive prediction temperature value and a preset greenhouse air temperature target value, adjusting operation parameters of the greenhouse equipment. By simulating thermal field distribution in a greenhouse and processing time sequence data of an external environment, a deterministic rule and random fluctuation are covered, a deviation value with a target value is calculated according to an obtained comprehensive prediction value, and equipment is dynamically adjusted based on prediction deviation, so that ineffective energy consumption and equipment loss are reduced.

The invention discloses a flow resistance and heat transfer simulation analysis method for a thermal management refrigerant side integrated module, and relates to the technical field of computer simulation. The method mainly comprises the following steps of: dividing a computational domain model into a solid domain, a fluid domain comprising a plurality of single-phase flow channel sub-domains and a flow channel section which is in a gas-liquid two-phase state and exchanges latent heat along with phase change in combination with the need of an actual analysis working condition; performing polynomial fitting on various parameters by fixing the inlet pressure value of each single-phase flow channel sub-domain; loading the fitted physical property function to the corresponding runner sub-domain, and setting a constant material attribute for the solid domain runner plate; a conjugate heat transfer model is started on an interface of a fluid domain and a solid domain, and interface heat flux density conservation and temperature continuity simulation is carried out; setting boundary conditions; and executing conjugate heat transfer simulation calculation until convergence calculation is completed. According to the method, the simulation precision is improved through fusion of three core technologies of dynamic change physical property fitting, solid-liquid conjugate heat transfer coupling and two-phase flow latent heat equivalent modeling.

The present invention relates to the technical field of electrodeposition, and relates to a simulation method for flow field distribution and deposition morphology in ultrafast laser-assisted electrochemical deposition. The steps of the method comprise: constructing, in multiphysics simulation software, a two-dimensional axisymmetric multiphysics coupled field model for heat transfer, solid and fluid heat transfer, tertiary current distribution, and laminar flow; constructing a geometric model of a deposition cell and a substrate, and setting laser properties, material physical parameters, and electrodeposition properties in the multiphysics simulation software; constructing an ultrafast laser heat transfer model on the basis of a two-temperature equation; setting initial and boundary conditions of the ultrafast laser heat transfer model, and constructing an electrodeposition field; coupling the ultrafast laser heat transfer model with the electrodeposition field to construct an ultrafast laser-assisted electrochemical deposition model; delineating a grid; and performing calculation and analysis. In the present invention, ultrafast laser is incorporated to perform multiphysics coupling of a thermal field, a flow field, an electric field, etc., and a two-temperature equation and tertiary current distribution are incorporated to the model, thereby achieving the accuracy and comprehensiveness of prediction models.

The invention relates to the technical field of comprehensive energy systems, in particular to a hydrothermal dynamic coupling method and system for a comprehensive energy heat supply pipe network. A dynamic hydraulic model and a dynamic thermal model are constructed by acquiring hydraulic parameter data and thermal parameter data of the heat supply pipe network, and an improved forward feedback iteration method (MFBI) is adopted to perform coupling solution on the two models to obtain the hydrothermal dynamic coupling characteristics of the heat supply pipe network of the comprehensive energy system. Wherein the dynamic hydraulic model is based on a fluid continuity equation and a motion equation, the dynamic thermodynamic model comprises a radial heat loss model and an axial heat transfer model, and the MFBI method effectively solves the problem of difference of hydraulic and thermodynamic parameters on the time scale by executing a plurality of hydraulic calculation step lengths in a thermodynamic calculation period. According to the method, the hydraulic dynamic change process in the heat supply pipe network at the initial stage of load change can be effectively simulated, the safety of the pipe network for dispatching optimization of the comprehensive energy system is improved, and technical support is provided for efficient and clean utilization of energy.

The invention belongs to the technical field of photo-thermal performance optimization, and relates to a photo-thermal performance optimization method based on an aerogel microstructure. Comprising the following steps: S1, establishing a microcosmic porous structure of aerogel: constructing an aerogel two-dimensional porous structure with a corresponding size based on a four-parameter random growth model; s2, simulating the solar radiation absorption and scattering characteristics of the tabular aerogel: simulating the transmittance of the tabular aerogel based on a Monte Carlo method, and calculating the solar radiation extinction coefficient of the aerogel; s3, simulating the heat transfer process of the aerogel based on a lattice Boltzmann model, and calculating the heat conductivity coefficient of the aerogel; and S4, constructing a dynamic heat transfer model, and simulating the energy consumption performance of the aerogel glass in an actual environment. According to the invention, the photo-thermal performance of the aerogel is accurately simulated, and the dynamic heat transfer model is combined to evaluate the energy consumption performance of the aerogel in an actual environment. By optimizing the microstructure of the aerogel, the photo-thermal performance and the energy efficiency of the aerogel are remarkably improved.

The invention belongs to the technical field of heat supply systems, and provides a heat supply system secondary network return water temperature prediction method and system based on indoor and outdoor temperature difference, and the method comprises the steps: obtaining the secondary network water supply temperature, the indoor temperature and the outdoor temperature of a heat supply system, and calculating the secondary network return water temperature of the heat supply system in combination with a heat transfer model; taking the obtained secondary network return water temperature as a state variable, and respectively constructing a state equation and an observation equation for predicting the secondary network return water temperature of the heat supply system; calculating an observed value of the secondary network return water temperature at the next moment according to the constructed state equation and observation equation; and respectively carrying out prediction updating on the constructed state equation and observation equation by adopting extended Kalman filtering to obtain an optimal secondary network return water temperature observation value at the next moment, namely completing the prediction of the secondary network return water temperature of the heat supply system.

The invention discloses an automatic shell-making wire environment simulation system. The system comprises an environmental parameter testing unit, a heat and mass transfer model establishing unit and an optimization processing unit. The environmental parameter testing unit is used for testing environmental parameters influencing the drying process of the shell-making drying cabin through testing equipment, evaluating the uniformity of airflow in the drying cabin and the change condition of the environmental parameters, and sending testing and evaluating results to the heat and mass transfer model establishing unit; the environmental parameters at least comprise wind speed. And the heat and mass transfer model building unit is used for building a shell drying heat transfer model and a shell drying mass transfer model, evaluating the shell drying heat transfer model and the shell drying mass transfer model based on the model expression indexes after building is completed, and analyzing the influence of the environmental parameters on shell heat transfer and mass transfer based on the information transmitted by the environmental parameter testing unit. And the optimization processing unit is used for introducing the influence of load, airflow in the drying cabin and air into the established shell drying heat transfer model and shell drying mass transfer model for simulation and optimization.

This invention provides a method for modeling the starting performance of a marine gas turbine. First, a gas turbine aero-thermodynamic performance calculation model is established using C++, and a heat transfer model, temperature sensor model, and control law model for the gas turbine's high-temperature components are established using the M language. Then, based on test data from the gas turbine startup process, the method analyzes how the pressure ratio and efficiency of typical gas turbine components change with the physical speed of the gas generator during startup. The corresponding low-speed characteristics of the gas turbine's rotating components are generated and corrected, enabling high-precision, real-time simulation of the gas turbine's starting performance. This method considers the heat exchange between the high-temperature fuel gas and the ambient atmosphere and the gas turbine itself, improving the accuracy of the gas turbine startup performance simulation. The method can provide a simulation testing tool for the design and optimization of gas turbine startup control laws.

The invention discloses an optimization method of a ground source heat pump, electronic equipment and a program product, and the method comprises the steps: collecting the operation data and environment data of a ground source heat pump system in real time through an edge computing gateway deployed on site; constructing a multi-objective optimization model of the ground source heat pump system on the cloud server; solving the optimization model by adopting a self-adaptive multi-target genetic algorithm, and outputting a Pareto optimal solution set; selecting a final execution scheme from the Pareto optimal solution set according to a preset decision preference weight, generating a control instruction, and issuing the control instruction to the field executor through the edge computing gateway; the soil temperature field evolution is predicted through the buried pipe heat transfer model, and a prediction result is fed back to the optimization model and used for correcting the soil heat balance objective function, and long-term dynamic optimization is achieved. According to the method, collaborative optimization of economy, environmental protection and sustainability can be realized by constructing the multi-objective optimization model fusing the operation cost, the soil heat balance and the carbon emission.

The invention discloses a calculation method and a calculation device for a film state boiling starting point of a surface with dirt, and belongs to the field of nuclear power. The calculation method for the membrane state boiling starting point of the surface with the dirt comprises the following steps: establishing a fuel rod cladding surface heat exchange model with the dirt according to a fuel rod cladding model with the dirt and thermal parameters, and calculating to obtain a heat conductivity coefficient and permeability of a dirt area; calculating the gas film thickness at the beginning of film boiling; according to the pressure balance and energy conservation equation, the heat flux corresponding to the minimum gas film thickness value is obtained through calculation and serves as the initial heat flux of film boiling. The method can accurately calculate the initial heat flux density of membrane boiling under the influence of dirt, and improves the precision of systematically analyzing the influence of dirt on the thermal hydraulic performance of a reactor.

The present invention discloses a multi-objective thermal-fluid topological design optimization method for the cooling element of a precision gear grinding machine tool, comprising the following steps: Step 1: Define the design domain: Expand the cooling element into a plane, define a two-dimensional design domain representing the cooling element's geometric structure, and discretize it using the finite element method; Step 2: Numerical modeling: Model the cooling element as a porous medium; Under the conditions of laminar incompressible flow, the fluid dynamics are governed by the dimensionless forms of the continuity equation and the momentum equation; The fluid-solid coupled heat transfer model is governed by the dimensionless energy conservation equation; Step 3: Construct an objective function: The optimization objective is defined as a weighted function of heat transfer and fluid dissipated power, and a fluid-solid heat transfer topological optimization model is constructed; Step 4: Solve the objective function; Step 5: Restore the shape and structure of the cooling element. The present invention also discloses a precision gear grinding machine tool and a cooling element.

Heating, ventilation and air conditioning (HVAC) systems and methods of use are described. The HVAC system includes at least one internal surface temperature sensor configured to provide an interior wall surface temperature measurement. The internal surface temperature sensor is positioned on an interior surface of an external wall of the residential house. The HVAC system also includes a control system in communication over a network with the internal surface temperature sensor. The control system is configured to obtain the interior wall surface temperature measurement and apply a home heat transfer model to determine a predicted space air temperature. The home heat transfer model is based on thermal dynamics of space air and building structure using the interior wall surface temperature measurement.